NOUMENOpen app

Qwen · Frontier

Qwen3.7 Max

Added May 21, 2026

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Use in the app

Qwen3.7 Max is built for agentic coding, office automation, and long-running tool workflows in non-thinking mode.

  • Reasoning
  • Tools
Input
Text
Output
Text
Reasoning effort
none · high
Discovery tier
Frontier

Pricing

USD per 1M tokens
Input
$1.47
Output
$4.43
Cache read
$0.30
Cache write
$1.84

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
65.5K

Side by side

Qwen3.7 Max compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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Qwen3.7 MaxQwenThis modelQwen3.7 Max ThinkingQwenRemove
ProviderQwenQwen
Discovery tierFrontierFrontier
AddedMay 21, 2026May 21, 2026
Limits
Context window1M1M
Max output65.54K65.54K
Pricing, USD per 1M tokens
Input$1.47$1.47
Output$4.43$4.43
Cache read$0.30$0.30
Cache write$1.84$1.84
Capabilities
ReasoningYesYes
ToolsYesYes
Reasoning effortnone, highnone, high

Public evaluations

Benchmarks

There are no public benchmark results for these models yet.

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Prompt cache hits
33.0%
About $1.09 per 1M input tokens with caching

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "qwen/qwen3.7-max",
    "reasoning_effort": "none",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="qwen/qwen3.7-max",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

Qwen

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